1. Field of the Invention
The present invention generally relates to an image registration method; particularly, the present invention relates to an image registration method that can increase the accuracy of image registrations.
2. Description of the Related Art
In the field of medical science, image registration is a very important process that is widely and heavily used in a majority of the planning, improvement, and assessment of surgical and radiotherapy processes. However, variations in appearance of data, image noise, and data distortions make the image registration process that much harder to complete, resulting in unstable and poor performance of conventional image registration methods.
In more definite terms in referring to the pathological image of FIG. 1A as an example, a specimen will first be cut into a plurality of slices, wherein each slice is fixed on a transparent slide. Then, tissue slides will be stained according to the user's requirements. Referring to the present figure as an example, routine H&E staining is used to perform histopathological analysis. After staining, the slices are arranged in serial order and then are digitalized through image scanning. After the digitalized pathological images are image registered, three-dimensional images of the specimen may be recreated by the users from the image registered pathological images. However, as shown in FIG. 1B, with respect to relatively more image noise occurring in pathological images, the results generated by conventional image registration methods are often subpar and/or unstable. In reference to FIG. 1B as an example of performing image registration according to the conventional SURF (Speeded-up Robust Features) method, the features PS detected in the source image S have been erroneously matched to completely different features PT in the target image. When the conventional image registration method proceeds to perform image transformations on the source image S according to the detected match points (PS & PT) in order to be more lined up with the structure in the target image, image source S will be transformed into an unrecognizable image due to the erroneous matching. However, even when other conventional image registration methods are employed—such as the UnwarpJ, Bunwarj, CLAHE+BunwarpJ, TrakEM2 methods of FIG. 1C—the other conventional image registration methods still cannot accurately transform the source image S to the coordinate system of the target image T. As such, a more accurate image registration method in inevitably required.